Employees Empowered to Build AI Agents
Gumloop, founded in mid-2023 by Max Brodeur-Urbas, has raised $50 million in Series B funding led by Benchmark. The startup develops a platform where employees can create autonomous AI agents without coding. These agents handle complex workflows such as onboarding, invoice reconciliation, support ticket triage, CRM updates, and RFP preparation.
The company’s mission is simple. It frees employees from repetitive tasks. Teams can focus on uniquely human work. Gumloop combines an intuitive user experience, access to multiple AI model providers, and embedded enterprise-grade security. This allows companies to deploy agents safely and at scale.
Leading organisations including Shopify, Ramp, Gusto, Samsara, Instacart, and Opendoor have adopted the platform. Employees can share the agents they build with colleagues. This sharing accelerates automation adoption and fosters internal AI-native culture. Brodeur-Urbas that “they get addicted, they start building more agents, and then all of a sudden, the whole company is AI native.”
The Series B funding will support Gumloop’s expansion. The startup plans to grow its engineering and sales teams to meet rising enterprise demand. Brodeur-Urbas initially envisioned a small, 10-person company. Growing adoption forced a broader scale-up. Benchmark general partner Everett Randle led the round. He believes Gumloop is a tool that empowers every employee with AI capabilities, unlocking productivity across organisations.
Randle’s due diligence revealed strong organic adoption. In one example, a client trialled Gumloop alongside two competitors. After six months, employees were actively using Gumloop daily, while the other platforms went largely unused. “You can go in and start making agents and workflow automations immediately,” Randle said.
Gumloop is deliberately model-agnostic. Teams can route tasks across providers including OpenAI, Anthropic, Google’s Gemini, or open-source alternatives. This flexibility allows companies to optimise for performance, cost, and data sensitivity while using existing AI credits efficiently.
Reliability and Simplicity
The platform is designed for non-technical users. Workflows are built using natural language and visual blocks. Guardrails include data scopes, approval checkpoints, human-in-the-loop handoffs, and deterministic tools such as search, databases, and APIs. Gumloop manages versioning, retries, monitoring, and audit logs. This ensures agents can move from pilot to production safely.
Enterprise-grade features include single sign-on, role-based access, data residency controls, and workflow-level policy enforcement. Pre-built templates allow teams to deploy agents for support triage, quote-to-cash operations, vendor onboarding, and catalogue management. Templates can be adapted in hours, not months, saving teams significant time.
Gumloop promotes collaboration. Employees can reuse templates and share agents. This approach enables faster automation adoption and demonstrates the value of bottoms-up AI deployment in enterprises.
Expanding Enterprise AI
Gumloop also introduced “Gumstack,” a security and monitoring infrastructure. Gumstack tracks AI usage across tools including ChatGPT, Claude, and Cursor. It monitors data in emails, chat, and SaaS applications. This ensures compliance and governance for all enterprise AI workflows.
The company faces competition from Zapier, n8n, Dust, and foundational AI labs such as Anthropic’s Claude Co-Work. Cloud providers are also adding agentic capabilities directly into productivity suites. Gumloop differentiates itself through usability, enterprise controls, and model flexibility.
Randle calls enterprise automation “a massive pot of gold.” He believes that empowering every employee to build AI agents unlocks significant productivity gains without bottlenecking on scarce developer time.
Model-Agnostic Flexibility
Gumloop’s model-agnostic platform lets enterprises assign tasks to the best AI model, expanding agent capabilities across workflows. Source: Created by Ventureburn.
Gumloop allows enterprises to assign tasks to the best AI model for the job. Finance teams may select smaller deterministic models for invoices, while support teams may opt for more capable models with strict retrieval and redaction features. This ensures maximum performance per dollar, not model loyalty.
Model independence also reduces platform risk. As AI models converge on similar capabilities, Gumloop’s orchestration layer—connectors, workflow logic, monitoring, and policies—becomes a durable enterprise asset.
The Series B will fund the expansion of proactive AI agent capabilities. Gumloop will grow Gumstack and extend enterprise-wide orchestration. Its platform allows employees to deploy agents across Slack, Microsoft Teams, and email without coding.
More News: Qdrant Raises $50 Million to Scale Composable Vector Search
Driving AI Adoption
Gumloop currently serves thousands of users at companies such as Shopify, Ramp, Gusto, Samsara, Instacart, and Opendoor. The platform allows teams to integrate multiple AI providers and build complex workflows without technical expertise.
By combining usability, enterprise controls, and flexible model options, Gumloop accelerates AI adoption in organisations. Employees can automate workflows, reduce repetitive work, and increase productivity across teams.
To stay updated on crypto venture capital funding and market trends, visit our venture capital news section for more insights.
